XModBench is a tri-modal benchmark that systematically measures cross-modal consistency, modality disparities, and directional imbalances in omni-language models across five task families and all modality combinations.
Cross-modal consistency in multimodal large language mod- els.arXiv preprint arXiv:2411.09273
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DMIL is a multimodal learning framework that decomposes sample-specific interactions into redundant, unique, and synergistic components via variational architecture and uses them for adaptive fine-tuning.
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XModBench: Benchmarking Cross-Modal Capabilities and Consistency in Omni-Language Models
XModBench is a tri-modal benchmark that systematically measures cross-modal consistency, modality disparities, and directional imbalances in omni-language models across five task families and all modality combinations.